
import os
from IPython.display import display, HTML
display(HTML("<style>.container { width:100% !important; }</style>"))


# If you want to run this notebook locally, copy the output of the next cell into the next line of this cell.
# antenna = "54"
# csv_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/_rtp_summary_'
# auto_metrics_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/auto_metrics_inspect'
# os.environ["ANTENNA"] = antenna
# os.environ["CSV_FOLDER"] = csv_folder
# os.environ["AUTO_METRICS_FOLDER"] = auto_metrics_folder


# Use environment variables to figure out path to the csvs and auto_metrics
antenna = os.environ["ANTENNA"]
csv_folder = os.environ["CSV_FOLDER"]
auto_metrics_folder = os.environ["AUTO_METRICS_FOLDER"]
print(f'antenna = "{antenna}"')
print(f'csv_folder = "{csv_folder}"')
print(f'auto_metrics_folder = "{auto_metrics_folder}"')

antenna = "87"
csv_folder = "/home/obs/src/H5C_Notebooks/_rtp_summary_"
auto_metrics_folder = "/home/obs/src/H5C_Notebooks/auto_metrics_inspect"


display(HTML(f'<h1 style=font-size:50px><u>Antenna {antenna} Report</u><p></p></h1>'))


import numpy as np
import pandas as pd
pd.set_option('display.max_rows', 1000)
import glob
import re
from hera_notebook_templates.utils import status_colors, Antenna


# load csvs and auto_metrics htmls in reverse chronological order
csvs = sorted(glob.glob(os.path.join(csv_folder, '*.csv')))[::-1]
print(f'Found {len(csvs)} csvs in {csv_folder}')
auto_metric_htmls = sorted(glob.glob(auto_metrics_folder + '/auto_metrics_inspect_*.html'))[::-1]
print(f'Found {len(auto_metric_htmls)} auto_metrics notebooks in {auto_metrics_folder}')

Found 104 csvs in /home/obs/src/H5C_Notebooks/_rtp_summary_
Found 100 auto_metrics notebooks in /home/obs/src/H5C_Notebooks/auto_metrics_inspect


# Per-season options
mean_round_modz_cut = 4
dead_cut = 0.4
crossed_cut = 0.0

def jd_to_summary_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H5C_Notebooks/blob/main/_rtp_summary_/rtp_summary_{jd}.html'

def jd_to_auto_metrics_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H5C_Notebooks/blob/main/auto_metrics_inspect/auto_metrics_inspect_{jd}.html'


this_antenna = None
jds = []

# parse information about antennas and nodes
for csv in csvs:
    df = pd.read_csv(csv)
    for n in range(len(df)):
        # Add this day to the antenna
        row = df.loc[n]
        antnum = row['Ant']
        if antnum != int(antenna):
            continue
            
        if this_antenna is None:
            this_antenna = Antenna(row['Ant'], row['Node'])
        jd = [int(s) for s in re.split('_|\.', csv) if s.isdigit()][-1]
        jds.append(jd)
        this_antenna.add_day(jd, row)
        break


# build dataframe
to_show = {'JDs': [f'<a href="{jd_to_summary_url(jd)}" target="_blank">{jd}</a>' for jd in jds]}
to_show['A Priori Status'] = [this_antenna.statuses[jd] for jd in jds]

df = pd.DataFrame(to_show)

# create bar chart columns for flagging percentages:
bar_cols = {}
bar_cols['Auto Metrics Flags'] = [this_antenna.auto_flags[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jee)'] = [this_antenna.dead_flags_Jee[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jnn)'] = [this_antenna.dead_flags_Jnn[jd] for jd in jds]
bar_cols['Crossed Fraction in Ant Metrics'] = [this_antenna.crossed_flags[jd] for jd in jds]
bar_cols['Flag Fraction Before Redcal'] = [this_antenna.flags_before_redcal[jd] for jd in jds]
bar_cols['Flagged By Redcal chi^2 Fraction'] = [this_antenna.redcal_flags[jd] for jd in jds]
for col in bar_cols:
    df[col] = bar_cols[col]

z_score_cols = {}
z_score_cols['ee Shape Modified Z-Score'] = [this_antenna.ee_shape_zs[jd] for jd in jds]
z_score_cols['nn Shape Modified Z-Score'] = [this_antenna.nn_shape_zs[jd] for jd in jds]
z_score_cols['ee Power Modified Z-Score'] = [this_antenna.ee_power_zs[jd] for jd in jds]
z_score_cols['nn Power Modified Z-Score'] = [this_antenna.nn_power_zs[jd] for jd in jds]
z_score_cols['ee Temporal Variability Modified Z-Score'] = [this_antenna.ee_temp_var_zs[jd] for jd in jds]
z_score_cols['nn Temporal Variability Modified Z-Score'] = [this_antenna.nn_temp_var_zs[jd] for jd in jds]
z_score_cols['ee Temporal Discontinuties Modified Z-Score'] = [this_antenna.ee_temp_discon_zs[jd] for jd in jds]
z_score_cols['nn Temporal Discontinuties Modified Z-Score'] = [this_antenna.nn_temp_discon_zs[jd] for jd in jds]
for col in z_score_cols:
    df[col] = z_score_cols[col]

ant_metrics_cols = {}
ant_metrics_cols['Average Dead Ant Metric (Jee)'] = [this_antenna.Jee_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Dead Ant Metric (Jnn)'] = [this_antenna.Jnn_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Crossed Ant Metric'] = [this_antenna.crossed_metrics[jd] for jd in jds]
for col in ant_metrics_cols:
    df[col] = ant_metrics_cols[col]

redcal_cols = {}
redcal_cols['Median chi^2 Per Antenna (Jee)'] = [this_antenna.Jee_chisqs[jd] for jd in jds]
redcal_cols['Median chi^2 Per Antenna (Jnn)'] = [this_antenna.Jnn_chisqs[jd] for jd in jds]   
for col in redcal_cols:
    df[col] = redcal_cols[col]

# style dataframe
table = df.style.hide_index()\
          .applymap(lambda val: f'background-color: {status_colors[val]}' if val in status_colors else '', subset=['A Priori Status']) \
          .background_gradient(cmap='viridis', vmax=mean_round_modz_cut * 3, vmin=0, axis=None, subset=list(z_score_cols.keys())) \
          .background_gradient(cmap='bwr_r', vmin=dead_cut-.25, vmax=dead_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .background_gradient(cmap='bwr_r', vmin=crossed_cut-.25, vmax=crossed_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .background_gradient(cmap='plasma', vmax=4, vmin=1, axis=None, subset=list(redcal_cols.keys())) \
          .applymap(lambda val: 'font-weight: bold' if val < dead_cut else '', subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val < crossed_cut else '', subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .applymap(lambda val: 'color: red' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .bar(subset=list(bar_cols.keys()), vmin=0, vmax=1) \
          .format({col: '{:,.4f}'.format for col in z_score_cols}) \
          .format({col: '{:,.4f}'.format for col in ant_metrics_cols}) \
          .format('{:,.2%}', na_rep='-', subset=list(bar_cols.keys())) \
          .set_table_styles([dict(selector="th",props=[('max-width', f'70pt')])])


display(HTML(f'<h2>Antenna {antenna}, Node {this_antenna.node}:</h2>'))
HTML(table.render(render_links=True, escape=False))


html_to_display = ''
for am_html in auto_metric_htmls:
    # read html into a list of lines
    with open(am_html) as f:
        lines = f.readlines()
    
    # find section with this antenna's metric plots and add to html_to_display
    jd = [int(s) for s in re.split('_|\.', am_html) if s.isdigit()][-1]
    try:
        section_start_line = lines.index(f'<h2>Antenna {antenna}: {jd}</h2>\n')
    except ValueError:
        continue
    html_to_display += lines[section_start_line].replace(str(jd), f'<a href="{jd_to_auto_metrics_url(jd)}" target="_blank">{jd}</a>')
    for line in lines[section_start_line + 1:]:
        html_to_display += line
        if '<hr' in line: 
            break


HTML(html_to_display)

JDs	A Priori Status	Auto Metrics Flags	Dead Fraction in Ant Metrics (Jee)	Dead Fraction in Ant Metrics (Jnn)	Crossed Fraction in Ant Metrics	Flag Fraction Before Redcal	Flagged By Redcal chi^2 Fraction	ee Shape Modified Z-Score	nn Shape Modified Z-Score	ee Power Modified Z-Score	nn Power Modified Z-Score	ee Temporal Variability Modified Z-Score	nn Temporal Variability Modified Z-Score	ee Temporal Discontinuties Modified Z-Score	nn Temporal Discontinuties Modified Z-Score	Average Dead Ant Metric (Jee)	Average Dead Ant Metric (Jnn)	Average Crossed Ant Metric	Median chi^2 Per Antenna (Jee)	Median chi^2 Per Antenna (Jnn)
2459594	digital_ok	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	0.450920	-0.343682	23.468246	5.653706	6.613930	1.664429	22.959022	5.262868	0.8146	0.8150	0.2314	16.949231	14.054437
2459593	digital_ok	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	272.873653	277.965932	inf	inf	58.072610	62.189792	322.221902	293.310899	nan	nan	nan	0.000000	0.000000
2459592	digital_ok	0.00%	100.00%	100.00%	0.00%	-	-	0.719397	-0.759152	1.175057	-0.501605	-0.323338	0.845090	-1.616843	0.150801	0.0337	0.0309	0.0014	nan	nan
2459591	digital_ok	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	0.892396	2.042648	31.856268	8.990006	0.258564	0.776946	0.321826	2.905074	0.6779	0.6942	0.3631	6.185399	6.392705
2459590	digital_ok	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	1.769179	2.145025	29.162721	8.913857	1.601193	1.082537	0.418673	1.670510	0.6803	0.6951	0.3574	5.449948	5.496685
2459589	digital_ok	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	0.831443	1.248085	25.718335	8.283069	8.573588	2.844993	14.891057	3.594267	0.7326	0.7284	0.2703	5.447849	5.201722
2459588	digital_ok	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	0.209876	1.689260	31.377286	9.935118	5.605004	0.909205	9.961649	2.448552	0.7974	0.7823	0.2033	13.997683	9.963773
2459587	digital_ok	100.00%	-	-	-	100.00%	0.00%	0.350956	2.503028	43.546878	13.848515	0.504574	1.238735	1.525332	4.965494	nan	nan	nan	8.996810	5.608917
2459586	digital_ok	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	3.275660	4.470411	13.002005	6.196917	6.777986	5.974908	2.642353	5.761569	0.6718	0.6888	0.3463	4.577666	4.260266
2459585	digital_ok	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	20.924590	16.785781	6.669372	5.899220	9.308946	9.035840	0.950701	1.534037	0.0346	0.0318	0.0010	0.000000	0.000000
2459584	digital_ok	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	17.714434	18.811429	32.679076	12.707782	2.660213	18.656441	0.289173	1.496708	0.6799	0.6909	0.3707	9.569829	7.838951
2459583	digital_ok	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	0.987081	1.729651	10.299808	8.224622	-0.584773	2.843337	0.096130	2.891922	0.6806	0.6843	0.3688	0.000000	0.000000
2459582	digital_ok	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	0.858902	1.718660	9.104525	7.821849	0.048529	1.002601	0.090509	2.310100	0.6797	0.6828	0.3740	4.157367	3.696142
2459581	digital_ok	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	1.523735	1.573128	10.796759	8.452126	-0.422532	0.867361	0.262466	5.003850	0.6929	0.6940	0.3670	3.903377	3.482522
2459580	digital_ok	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	1.092602	1.776085	10.631999	8.662903	0.497373	0.792446	-0.002660	4.974337	0.6850	0.6890	0.3652	4.208481	3.464407
2459579	digital_ok	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	1.261255	1.314770	12.243300	10.399372	-0.077154	0.910776	0.538228	4.804826	0.6812	0.6884	0.3699	5.610837	5.103146
2459578	digital_ok	100.00%	100.00%	100.00%	0.00%	-	-	nan	nan	inf	inf	nan	nan	nan	nan	nan	nan	nan	nan	nan
2459577	digital_ok	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	1.596264	1.411019	9.941245	7.939221	-0.310854	0.951040	0.054772	4.768916	0.6873	0.6917	0.3670	4.111178	3.670120
2459576	digital_ok	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	1.377356	0.634292	7.870828	6.646558	0.154159	0.681789	0.114492	2.694254	0.7051	0.7139	0.3705	4.823554	4.489596
2459575	digital_ok	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	0.964988	0.936218	7.211347	5.882730	5.902510	5.039771	12.120273	7.996349	0.7723	0.7728	0.3070	6.834613	6.376818
2459574	digital_ok	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	nan	nan	inf	inf	nan	nan	nan	nan	nan	nan	nan	0.000000	0.000000
2459573	digital_ok	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	0.987242	0.604523	13.349615	8.821430	-0.293156	1.294432	0.131682	3.404661	0.7001	0.7100	0.3653	4.329673	3.957394
2459572	digital_ok	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	0.858192	1.007942	7.545159	5.385229	0.284652	0.769369	1.025883	5.850537	0.7027	0.7091	0.3660	5.885282	4.761922
2459571	digital_ok	0.00%	100.00%	100.00%	0.00%	-	-	0.268368	-0.327211	-0.384441	-0.601585	-0.978768	0.028325	1.305350	0.146998	0.0569	0.0349	0.0106	nan	nan
2459570	digital_ok	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	6.096454	4.270331	6.269689	4.356875	3.979759	3.200234	2.599160	3.244803	0.7099	0.7217	0.3376	7.996790	6.880254
2459569	digital_ok	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	2.240090	1.144709	8.958201	6.237639	13.146651	7.210824	11.541298	7.981743	0.7823	0.7858	0.2139	8.519930	6.137218
2459566	digital_ok	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	1.014918	1.154859	9.970029	8.092679	-0.921016	0.617791	1.156276	5.425828	0.6888	0.6949	0.3817	3.824179	3.348393
2459565	digital_ok	100.00%	-	-	-	100.00%	0.00%	nan	nan	inf	inf	nan	nan	nan	nan	nan	nan	nan	0.000000	0.000000
2459564	digital_ok	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	1.104052	1.569932	10.852149	3.636033	0.748396	6.903016	0.324563	1.638057	0.7167	0.7237	0.3788	3.306741	2.978393
2459563	digital_ok	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	0.502366	1.411327	20.924242	4.903384	-0.060258	1.857915	0.175411	2.881794	0.7023	0.7164	0.3798	4.879116	4.474995
2459562	digital_ok	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	0.532588	0.867628	5.502689	4.613320	0.646414	0.419366	1.196652	1.805624	0.7078	0.7160	0.3694	3.214364	2.804160
2459561	digital_ok	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	0.298750	0.574624	5.067082	4.145857	0.009469	-0.456075	0.843045	2.226985	0.7078	0.7190	0.3632	3.155771	2.894418
2459560	digital_ok	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	0.607065	0.781551	5.369892	4.255559	0.599995	-0.392389	0.776354	2.132268	0.6982	0.7060	0.3795	3.118973	2.820127
2459559	digital_ok	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	0.718552	1.156287	5.714599	4.553533	0.272467	-0.265718	0.899097	2.302220	0.7087	0.7150	0.3612	3.043453	2.763396
2459558	digital_ok	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	0.671878	0.726238	10.352465	8.424667	-0.341553	1.609261	0.266027	3.189349	0.7102	0.7120	0.3697	3.953072	3.322105
2459557	digital_ok	-	100.00%	100.00%	0.00%	-	-	nan	nan	nan	nan	nan	nan	nan	nan	0.0309	0.0293	0.0011	nan	nan
2459556	digital_ok	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	0.827902	0.755842	11.268154	9.421273	-0.438208	0.948631	1.743521	5.002081	0.7095	0.7137	0.3662	3.818358	3.258646
2459554	digital_ok	-	0.00%	0.00%	0.00%	-	-	nan	nan	nan	nan	nan	nan	nan	nan	0.7103	0.7133	0.3810	nan	nan
2459553	digital_ok	-	0.00%	0.00%	0.00%	-	-	nan	nan	nan	nan	nan	nan	nan	nan	0.7131	0.7165	0.3765	nan	nan
2459552	digital_ok	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	0.793110	1.348656	15.062868	12.354622	1.923474	-0.638907	0.889154	1.716628	0.7212	0.7139	0.3692	8.837357	8.238315
2459551	digital_ok	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	0.730493	1.089440	6.499839	4.664392	0.248025	-0.849506	0.766319	2.336751	0.7130	0.7048	0.3651	3.506431	2.875926
2459550	digital_ok	-	99.18%	99.18%	0.00%	-	-	nan	nan	nan	nan	nan	nan	nan	nan	0.0476	0.0430	0.0021	nan	nan
2459549	digital_ok	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	0.521774	1.470803	11.787863	8.387435	-0.729462	1.105043	0.387966	2.841558	0.7120	0.7111	0.3709	3.706270	3.153494
2459542	digital_ok	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	1.269506	1.756429	24.697736	5.577513	-0.326180	4.019689	2.032854	1.479957	0.7616	0.7682	0.3304	3.453797	2.986738
2459541	digital_ok	100.00%	1.79%	1.79%	0.00%	100.00%	0.00%	0.421788	0.275298	13.195418	10.097744	26.855588	15.504398	13.753369	9.817440	0.7541	0.7490	0.3013	5.304064	4.457969
2459540	digital_ok	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	0.161384	1.165124	5.432437	3.900025	1.295892	5.765813	1.345504	2.892534	0.7568	0.7575	0.3154	3.395422	2.996453
2459536	digital_ok	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	1.710128	1.949843	21.243447	16.329931	1.904395	1.372187	6.388111	16.646071	0.7445	0.7431	0.3985	4.240826	3.585774
2459535	digital_ok	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	1.024867	0.781007	5.116418	3.308190	2.317034	5.271914	2.223241	4.960878	0.7809	0.7688	0.3389	3.470723	2.979805
2459534	digital_ok	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	-0.110461	0.509954	4.817969	2.771992	1.146990	4.913197	1.050831	2.873050	0.7679	0.7590	0.3481	8.780665	8.482835
2459533	digital_ok	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	1.092473	0.599970	11.018342	7.457309	0.278237	3.030702	2.234626	5.800575	0.7193	0.7225	0.3861	3.152093	2.896467
2459532	digital_ok	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	1.481593	1.084797	15.130003	11.028881	-0.807703	3.989571	1.444218	4.440335	0.7241	0.7203	0.3831	4.057941	3.549059
2459530	digital_ok	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	0.352911	0.774002	4.901655	3.502931	-0.230496	0.501689	2.221793	4.417370	0.7421	0.7330	0.3857	3.337461	2.969066
2459527	digital_ok	0.00%	-	-	-	100.00%	0.00%	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	0.000000	0.000000
2459524	digital_ok	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	2.331389	2.567758	14.722319	9.590000	6.629301	5.660743	0.929101	3.034391	0.9146	0.9453	0.2616	0.000000	0.000000
2459523	digital_ok	100.00%	-	-	-	100.00%	0.00%	0.854400	0.815998	17.407433	12.432880	1.645637	6.659978	2.058827	4.297347	nan	nan	nan	5.356576	4.433106
2459522	digital_ok	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	0.604672	1.145521	16.045437	11.785995	0.459985	4.045376	3.652636	8.925592	0.7060	0.7080	0.3142	3.764377	3.425281
2459513	digital_ok	0.00%	100.00%	100.00%	0.00%	-	-	0.468592	-0.118623	-0.333567	-0.625184	-0.500219	0.030408	1.458871	0.602362	0.0618	0.0461	0.0117	nan	nan
2459508	digital_ok	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	3.818540	3.499383	11.670895	7.911588	6.939365	4.153717	13.486846	11.439357	0.9278	0.9618	0.1405	0.000000	0.000000
2459505	digital_ok	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	1.577350	2.673812	14.404605	12.008751	1.794131	0.992994	5.937750	7.092293	0.8834	0.8722	0.1908	13.523004	14.216086
2459503	digital_ok	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	8.874077	7.335672	18.160803	13.458303	19.569921	15.747677	5.056276	4.385958	0.8854	0.8822	0.4153	0.000000	0.000000
2459501	digital_ok	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	5.087766	3.898702	11.829724	7.690021	11.062780	9.886794	1.762476	2.143372	0.8926	0.9205	0.3563	0.000000	0.000000
2459500	digital_ok	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	7.309496	4.640344	11.537780	7.136228	11.832122	8.510880	3.484820	2.520120	0.9000	0.9159	0.3448	0.000000	0.000000
2459499	digital_ok	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	8.935748	6.462284	15.173486	10.312650	13.001222	10.408843	6.597073	9.096999	0.9013	0.9472	0.1566	0.000000	0.000000
2459498	digital_ok	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	9.368253	7.293016	13.901934	10.429010	12.986822	11.174685	6.407798	5.104275	0.9111	0.9210	0.3718	0.000000	0.000000
2459497	digital_ok	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	12.085467	9.223036	15.393461	11.216551	17.460861	14.505553	8.790355	5.735963	0.9203	0.9405	0.3230	0.000000	0.000000
2459496	digital_ok	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	12.624956	9.143780	14.273536	9.817788	15.604420	12.987692	3.071008	3.368833	0.8895	0.9019	0.3679	0.000000	0.000000
2459495	digital_ok	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	10.124456	6.960521	12.804376	8.147606	13.138658	9.998107	3.381943	3.301742	0.8872	0.8974	0.4107	0.000000	0.000000
2459494	digital_ok	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	9.496840	6.995124	13.282070	8.766073	13.358607	11.434176	6.728125	4.492561	0.8855	0.8933	0.4219	0.000000	0.000000
2459492	digital_ok	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	1.504041	1.252839	15.976312	13.127629	1.336559	2.093985	9.441528	12.652043	0.7594	0.7990	0.3174	0.000000	0.000000
2459491	digital_ok	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	2.762240	2.519207	18.064405	14.864651	3.453537	4.308035	10.137011	15.285727	0.7939	0.8130	0.2591	0.000000	0.000000
2459490	digital_ok	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	3.018772	1.284878	18.683863	14.915858	2.054783	1.706156	11.320766	14.120549	0.7505	0.7996	0.3551	0.000000	0.000000
2459489	digital_ok	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	2.294027	1.048664	17.423093	13.684081	4.177730	3.130282	11.620995	14.206820	0.7674	0.8062	0.3046	0.000000	0.000000
2459488	digital_ok	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	2.941749	-0.118120	14.435317	10.613880	0.084204	1.602322	6.168190	15.465925	0.7683	0.8091	0.3358	0.000000	0.000000

Antenna Season Report Notebook¶

Antenna 87 Report

Load relevant info from summary CSVs¶

Table 1: Per-Night RTP Summary Info For This Atenna¶

Antenna 87, Node 8:

Load antenna metric spectra and waterfalls from auto_metrics notebooks.¶

Figure 1: Antenna autocorrelation metric spectra and waterfalls.¶

Antenna 87: 2459628

Antenna 87: 2459627

Antenna 87: 2459626

Antenna 87: 2459625

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Antenna 87: 2459536

Load antenna metric spectra and waterfalls from `auto_metrics` notebooks.¶